This chapter sets out the standardised approach for counterparty credit risk (SACCR).
The Standardised Approach for Counterparty Credit Risk (SACCR) applies to overthecounter (OTC) derivatives, exchangetraded derivatives and long settlement transactions. Banks that do not have approval to apply the internal model method (IMM) for the relevant transactions must use SACCR, as set out in this chapter. EAD is to be calculated separately for each netting set (as set out in CRE50.15, each transaction that is not subject to a legally enforceable bilateral netting arrangement that is recognised for regulatory capital purposes should be interpreted as its own netting set). It is determined using the following formula, where:
alpha = 1.4
The replacement cost (RC) and the potential future exposure (PFE) components are calculated differently for margined and unmargined netting sets. Margined netting sets are netting sets covered by a margin agreement under which the bank’s counterparty has to post variation margin; all other netting sets, including those covered by a oneway margin agreement where only the bank posts variation margin, are treated as unmargined for the purposes of the SACCR. The EAD for a margined netting set is capped at the EAD of the same netting set calculated on an unmargined basis.
For unmargined transactions, the RC intends to capture the loss that would occur if a counterparty were to default and were closed out of its transactions immediately. The PFE addon represents a potential conservative increase in exposure over a oneyear time horizon from the present date (ie the calculation date).
For margined trades, the RC intends to capture the loss that would occur if a counterparty were to default at the present or at a future time, assuming that the closeout and replacement of transactions occur instantaneously. However, there may be a period (the margin period of risk) between the last exchange of collateral before default and replacement of the trades in the market. The PFE addon represents the potential change in value of the trades during this time period.
In both cases, the haircut applicable to noncash collateral in the replacement cost formulation represents the potential change in value of the collateral during the appropriate time period (one year for unmargined trades and the margin period of risk for margined trades).
For capital adequacy purposes, banks may net transactions (eg when determining the RC component of a netting set) subject to novation under which any obligation between a bank and its counterparty to deliver a given currency on a given value date is automatically amalgamated with all other obligations for the same currency and value date, legally substituting one single amount for the previous gross obligations. Banks may also net transactions subject to any legally valid form of bilateral netting not covered in the preceding sentence, including other forms of novation. In every such case where netting is applied, a bank must satisfy its national supervisor that it has:
A netting contract with the counterparty or other agreement which creates a single legal obligation, covering all included transactions, such that the bank would have either a claim to receive or obligation to pay only the net sum of the positive and negative marktomarket values of included individual transactions in the event a counterparty fails to perform due to any of the following: default, bankruptcy, liquidation or similar circumstances.1
Written and reasoned legal reviews that, in the event of a legal challenge, the relevant courts and administrative authorities would find the bank’s exposure to be such a net amount under:
The law of the jurisdiction in which the counterparty is chartered and, if the foreign branch of a counterparty is involved, then also under the law of the jurisdiction in which the branch is located;
The law that governs the individual transactions; and
The law that governs any contract or agreement necessary to effect the netting.
Procedures in place to ensure that the legal characteristics of netting arrangements are kept under review in light of the possible changes in relevant law.
The national supervisor, after consultation when necessary with other relevant supervisors, must be satisfied that the netting is enforceable under the laws of each of the relevant jurisdictions. Thus, if any of these supervisors is dissatisfied about enforceability under its laws, the netting contract or agreement will not meet this condition and neither counterparty could obtain supervisory benefit.
There are two formulations of replacement cost depending on whether the trades with a counterparty are margined or unmargined. The margined formulation could apply both to bilateral transactions and to central clearing relationships. The formulation also addresses the various arrangements that a bank may have to post and/or receive collateral that may be referred to as initial margin.
For unmargined transactions, RC is defined as the greater of: (i) the current market value of the derivative contracts less net haircut collateral held by the bank (if any), and (ii) zero. This is consistent with the use of replacement cost as the measure of current exposure, meaning that when the bank owes the counterparty money it has no exposure to the counterparty if it can instantly replace its trades and sell collateral at current market prices. The formula for RC is as follows, where:
V is the value of the derivative transactions in the netting set
For the purpose of CRE52.10 above, the value of noncash collateral posted by the bank to its counterparty is increased and the value of the noncash collateral received by the bank from its counterparty is decreased using haircuts (which are the same as those that apply to repostyle transactions) for the time periods described in CRE52.5 above.
The formulation set out in CRE52.10 above, does not permit the replacement cost, which represents today’s exposure to the counterparty, to be less than zero. However, banks sometimes hold excess collateral (even in the absence of a margin agreement) or have outofthemoney trades which can further protect the bank from the increase of the exposure. As discussed in CRE52.21 to CRE52.23 below, the SACCR allows such overcollateralisation and negative marktomarket value to reduce PFE, but they are not permitted to reduce replacement cost.
The RC formula for margined transactions builds on the RC formula for unmargined transactions. It also employs concepts used in standard margining agreements, as discussed more fully below.
The RC for margined transactions in the SACCR is defined as the greatest exposure that would not trigger a call for VM, taking into account the mechanics of collateral exchanges in margining agreements.3 Such mechanics include, for example, “Threshold”, “Minimum Transfer Amount” and “Independent Amount” in the standard industry documentation,4 which are factored into a call for VM.5 A defined, generic formulation has been created to reflect the variety of margining approaches used and those being considered by supervisors internationally.
One objective of the SACCR is to reflect the effect of margining agreements and the associated exchange of collateral in the calculation of CCR exposures. The following paragraphs address how the exchange of collateral is incorporated into the SACCR.
To avoid confusion surrounding the use of terms initial margin and independent amount which are used in various contexts and sometimes interchangeably, the term independent collateral amount (ICA) is introduced. ICA represents: (i) collateral (other than VM) posted by the counterparty that the bank may seize upon default of the counterparty, the amount of which does not change in response to the value of the transactions it secures and/or (ii) the Independent Amount (IA) parameter as defined in standard industry documentation. ICA can change in response to factors such as the value of the collateral or a change in the number of transactions in the netting set.
Because both a bank and its counterparty may be required to post ICA, it is necessary to introduce a companion term, net independent collateral amount (NICA), to describe the amount of collateral that a bank may use to offset its exposure on the default of the counterparty. NICA does not include collateral that a bank has posted to a segregated, bankruptcy remote account, which presumably would be returned upon the bankruptcy of the counterparty. That is, NICA represents any collateral (segregated or unsegregated) posted by the counterparty less the unsegregated collateral posted by the bank. With respect to IA, NICA takes into account the differential of IA required for the bank minus IA required for the counterparty.
For margined trades, the replacement cost is calculated using the following formula, where:
V and C are defined as in the unmargined formulation, except that C now includes the net variation margin amount, where the amount received by the bank is accounted with a positive sign and the amount posted by the bank is accounted with a negative sign
TH is the positive threshold before the counterparty must send the bank collateral
MTA is the minimum transfer amount applicable to the counterparty
TH + MTA – NICA represents the largest exposure that would not trigger a VM call and it contains levels of collateral that need always to be maintained. For example, without initial margin or IA, the greatest exposure that would not trigger a variation margin call is the threshold plus any minimum transfer amount. In the adapted formulation, NICA is subtracted from TH + MTA. This makes the calculation more accurate by fully reflecting both the actual level of exposure that would not trigger a margin call and the effect of collateral held and/or posted by a bank. The calculation is floored at zero, recognising that the bank may hold NICA in excess of TH + MTA, which could otherwise result in a negative replacement cost.
The PFE addon consists of: (i) an aggregate addon component; and (ii) a multiplier that allows for the recognition of excess collateral or negative marktomarket value for the transactions within the netting set. The formula for PFE is as follows, where:
AddOnaggregate is the aggregate addon component (see CRE52.25 below)
multiplier is defined as a function of three inputs: V, C and AddOnaggregate
As a general principle, overcollateralisation should reduce capital requirements for counterparty credit risk. In fact, many banks hold excess collateral (ie collateral greater than the net market value of the derivatives contracts) precisely to offset potential increases in exposure represented by the addon. As discussed in CRE52.10 and CRE52.18, collateral may reduce the replacement cost component of the exposure under the SACCR. The PFE component also reflects the riskreducing property of excess collateral.
For prudential reasons, the Basel Committee decided to apply a multiplier to the PFE component that decreases as excess collateral increases, without reaching zero (the multiplier is floored at 5% of the PFE addon). When the collateral held is less than the net market value of the derivative contracts (“undercollateralisation”), the current replacement cost is positive and the multiplier is equal to one (ie the PFE component is equal to the full value of the aggregate addon). Where the collateral held is greater than the net market value of the derivative contracts (“overcollateralisation”), the current replacement cost is zero and the multiplier is less than one (ie the PFE component is less than the full value of the aggregate addon).
This multiplier will also be activated when the current value of the derivative transactions is negative. This is because outofthemoney transactions do not currently represent an exposure and have less chance to go inthemoney. The formula for the multiplier is as follows, where:
exp(…) is the exponential function
Floor is 5%
V is the value of the derivative transactions in the netting set
C is the haircut value of net collateral held
To calculate the aggregate addon, banks must calculate addons for each asset class within the netting set. The SACCR uses the following five asset classes:
Interest rate derivatives
Foreign exchange derivatives
Credit derivatives
Equity derivatives.
Commodity derivatives
Diversification benefits across asset classes are not recognised. Instead, the respective addons for each asset class are simply aggregated using the following formula (where the sum is across the asset classes):
The designation of a derivative transaction to an asset class is to be made on the basis of its primary risk driver. Most derivative transactions have one primary risk driver, defined by its reference underlying instrument (eg an interest rate curve for an interest rate swap, a reference entity for a credit default swap, a foreign exchange rate for a foreign exchange (FX) call option, etc). When this primary risk driver is clearly identifiable, the transaction will fall into one of the asset classes described above.
For more complex trades that may have more than one risk driver (eg multiasset or hybrid derivatives), banks must take sensitivities and volatility of the underlying into account for determining the primary risk driver.
Bank supervisors may also require more complex trades to be allocated to more than one asset class, resulting in the same position being included in multiple classes. In this case, for each asset class to which the position is allocated, banks must determine appropriately the sign and delta adjustment of the relevant risk driver (the role of delta adjustments in SACCR is outlined further in CRE52.30 below).
For each transaction, the primary risk factor or factors need to be determined and attributed to one or more of the five asset classes: interest rate, foreign exchange, credit, equity or commodity. The addon for each asset class is calculated using assetclassspecific formulas.6
Although the formulas for the asset class addons vary between asset classes, they all use the following general steps:
The effective notional (D) must be calculated for each derivative (ie each individual trade) in the netting set. The effective notional is a measure of the sensitivity of the trade to movements in underlying risk factors (ie interest rates, exchange rates, credit spreads, equity prices and commodity prices). The effective notional is calculated as the product of the following parameters (ie D = d * MF * δ):
The adjusted notional (d). The adjusted notional is a measure of the size of the trade. For derivatives in the foreign exchange asset class this is simply the notional value of the foreign currency leg of the derivative contract, converted to the domestic currency. For derivatives in the equity and commodity asset classes, it is simply the current price of the relevant share or unit of commodity multiplied by the number of shares/units that the derivative references. For derivatives in the interest rate and credit asset classes, the notional amount is adjusted by a measure of the duration of the instrument to account for the fact that the value of instruments with longer durations are more sensitive to movements in underlying risk factors (ie interest rates and credit spreads).
The maturity factor (MF). The maturity factor is a parameter that takes account of the time period over which the potential future exposure is calculated. The calculation of the maturity factor varies depending on whether the netting set is margined or unmargined.
The supervisory delta (δ). The supervisory delta is used to ensure that the effective notional take into account the direction of the trade, ie whether the trade is long or short, by having a positive or negative sign. It is also takes into account whether the trade has a nonlinear relationship with the underlying risk factor (which is the case for options and collateralised debt obligation tranches).
A supervisory factor (SF) is identified for each individual trade in the netting set. The supervisory factor is the supervisory specified change in value of the underlying risk factor on which the potential future exposure calculation is based, which has been calibrated to take into account the volatility of underlying risk factors.
The trades within each asset class are separated into supervisory specified hedging sets. The purpose of the hedging sets is to group together trades within the netting set where long and short positions should be permitted to offset each other in the calculation of potential future exposure.
Aggregation formulas are applied to aggregate the effective notionals and supervisory factors across all trades within each hedging set and finally at the assetclass level to give the asset class level addon. The method of aggregation varies between asset classes and for credit, equity and commodity derivatives it also involves the application of supervisory correlation parameters to capture diversification of trades and basis risk.
There are four time period parameters that are used in the SACCR (all expressed in years):
For all asset classes, the maturity M_{i} of a contract is the time period (starting today) until the latest day when the contract may still be active. This time period appears in the maturity factor defined in CRE52.48 to CRE52.53 that scales down the adjusted notionals for unmargined trades for all asset classes. If a derivative contract has another derivative contract as its underlying (for example, a swaption) and may be physically exercised into the underlying contract (ie a bank would assume a position in the underlying contract in the event of exercise), then maturity of the contract is the time period until the final settlement date of the underlying derivative contract.
For interest rate and credit derivatives, S_{i} is the period of time (starting today) until start of the time period referenced by an interest rate or credit contract. If the derivative references the value of another interest rate or credit instrument (eg swaption or bond option), the time period must be determined on the basis of the underlying instrument. S_{i} appears in the definition of supervisory duration defined in CRE52.34.
For interest rate and credit derivatives, E_{i} is the period of time (starting today) until the end of the time period referenced by an interest rate or credit contract. If the derivative references the value of another interest rate or credit instrument (eg swaption or bond option), the time period must be determined on the basis of the underlying instrument. E_{i} appears in the definition of supervisory duration defined in CRE52.34. In addition, E_{i} is used for allocating derivatives in the interest rate asset class to maturity buckets, which are used in the calculation of the asset class addon (see CRE52.57(3)).
Table 1 includes example transactions and provides each transaction’s related maturity M_{i}, start date S_{i} and end date E_{i}. In addition, the option delta in CRE52.38 to CRE52.41 depends on the latest contractual exercise date T_{i} (not separately shown in the table).

Table 1 

Instrument 
M_{i} 
S_{i} 
E_{i} 

Interest rate or credit default swap maturing in 10 years 
10 years 
0 
10 years 

10year interest rate swap, forward starting in 5 years 
15 years 
5 years 
15 years 

Forward rate agreement for time period starting in 6 months and ending in 12 months 
1 year 
0.5 year 
1 year 

Cashsettled European swaption referencing 5year interest rate swap with exercise date in 6 months 
0.5 year 
0.5 year 
5.5 years 

Physicallysettled European swaption referencing 5year interest rate swap with exercise date in 6 months 
5.5 years 
0.5 year 
5.5 years 

10year Bermudan swaption with annual exercise dates 
10 years 
1 year 
10 years 

Interest rate cap or floor specified for semiannual interest rate with maturity 5 years 
5 years 
0 
5 years 

Option on a bond maturing in 5 years with the latest exercise date in 1 year 
1 year 
1 year 
5 years 

3month Eurodollar futures that matures in 1 year 
1 year 
1 year 
1.25 years 

Futures on 20year treasury bond that matures in 2 years 
2 years 
2 years 
22 years 

6month option on 2year futures on 20year treasury bond 
2 years 
2 years 
22 years 

The adjusted notionals are defined at the trade level and take into account both the size of a position and its maturity dependency, if any.
For interest rate and credit derivatives, the tradelevel adjusted notional is the product of the trade notional amount, converted to the domestic currency, and the supervisory duration SD_{i} which is given by the formula below (ie d_{i} = notional * SD_{i}). The calculated value of SD_{i} is floored at ten business days.7 If the start date has occurred (eg an ongoing interest rate swap), S_{i} must be set to zero.
For foreign exchange derivatives, the adjusted notional is defined as the notional of the foreign currency leg of the contract, converted to the domestic currency. If both legs of a foreign exchange derivative are denominated in currencies other than the domestic currency, the notional amount of each leg is converted to the domestic currency and the leg with the larger domestic currency value is the adjusted notional amount.
For equity and commodity derivatives, the adjusted notional is defined as the product of the current price of one unit of the stock or commodity (eg a share of equity or barrel of oil) and the number of units referenced by the trade.
In many cases the trade notional amount is stated clearly and fixed until maturity. When this is not the case, banks must use the following rules to determine the trade notional amount.
Where the notional is a formula of market values, the bank must enter the current market values to determine the trade notional amount.
For all interest rate and credit derivatives with variable notional amounts specified in the contract (such as amortising and accreting swaps), banks must use the average notional over the remaining life of the derivative as the trade notional amount. The average should be calculated as “time weighted”. The averaging described in this paragraph does not cover transactions where the notional varies due to price changes (typically, FX, equity and commodity derivatives).
Leveraged swaps must be converted to the notional of the equivalent unleveraged swap, that is, where all rates in a swap are multiplied by a factor, the stated notional must be multiplied by the factor on the interest rates to determine the trade notional amount.
For a derivative contract with multiple exchanges of principal, the notional is multiplied by the number of exchanges of principal in the derivative contract to determine the trade notional amount.
For a derivative contract that is structured such that on specified dates any outstanding exposure is settled and the terms are reset so that the fair value of the contract is zero, the remaining maturity equals the time until the next reset date.
The supervisory delta adjustment (𝛿_{i}) parameters are also defined at the trade level and are applied to the adjusted notional amounts to reflect the direction of the transaction and its nonlinearity.
The delta adjustments for all instruments that are not options and are not collateralised debt obligation (CDO) tranches are as set out in the table below:8

Long in the primary risk factor 
Short in the primary risk factor 
Instruments that are not options or CDO tranches 
+1 
1 
The delta adjustments for options are set out in the table below, where:
The following are parameters that banks must determine appropriately:
P_{i} : Underlying price (spot, forward, average, etc)
K_{i} : Strike price
T_{i} : Latest contractual exercise date of the option
The supervisory volatility σ_{i} of an option is specified on the basis of supervisory factor applicable to the trade (see Table 2 in CRE52.72).
The symbol Φ represents the standard normal cumulative distribution function.

Bought 
Sold 
Call Options 


Put Options 


The delta adjustments for CDO tranches9 are set out in the table below, where the following are parameters that banks must determine appropriately:
A_{i} : Attachment point of the CDO tranche
D_{i} : Detachment point of the CDO tranche

Purchased (long protection) 
Sold (short protection) 
CDO tranches 


For singlepayment options the effective notional (ie D = d * MF * δ) is calculated using the following specifications:
For European, Asian, American and Bermudan put and call options, the supervisory delta must be calculated using the simplified BlackScholes formula referenced in CRE52.40. In the case of Asian options, the underlying price must be set equal to the current value of the average used in the payoff. In the case of American and Bermudan options, the latest allowed exercise date must be used as the exercise date T_{i} in the formula.
For Bermudan swaptions, the start date S_{i} must be equal to the earliest allowed exercise date, while the end date E_{i} must be equal to the end date of the underlying swap.
For digital options, the payoff of each digital option (bought or sold) with strike K_{i} must be approximated via the “collar” combination of bought and sold European options of the same type (call or put), with the strikes set equal to 0.95∙K_{i} and 1.05∙K_{i}. The size of the position in the collar components must be such that the digital payoff is reproduced exactly outside the region between the two strikes. The effective notional is then computed for the bought and sold European components of the collar separately, using the option formulae for the supervisory delta referenced in CRE52.40 (the exercise date T_{i} and the current value of the underlying P_{i} of the digital option must be used). The absolute value of the digitaloption effective notional must be capped by the ratio of the digital payoff to the relevant supervisory factor.
If a trade’s payoff can be represented as a combination of European option payoffs (eg collar, butterfly/calendar spread, straddle, strangle), each European option component must be treated as a separate trade.
For the purposes of effective notional calculations, multiplepayment options may be represented as a combination of singlepayment options. In particular, interest rate caps/floors may be represented as the portfolio of individual caplets/floorlets, each of which is a European option on the floating interest rate over a specific coupon period. For each caplet/floorlet, S_{i} and T_{i} are the time periods starting from the current date to the start of the coupon period, while E_{i} is the time period starting from the current date to the end of the coupon period.
Supervisory factors (SF_{i}) are used, together with aggregation formulas, to convert effective notional amounts into the addon for each hedging set.10 The way in which supervisory factors are used within the aggregation formulas varies between asset classes. The supervisory factors are listed in Table 2 under CRE52.72.
The hedging sets in the different asset classes are defined as follows, except for those described in CRE52.46 and CRE52.47:
Interest rate derivatives consist of a separate hedging set for each currency.
FX derivatives consist of a separate hedging set for each currency pair.
Credit derivatives consist of a single hedging set.
Equity derivatives consist of a single hedging set.
Commodity derivatives consist of four hedging sets defined for broad categories of commodity derivatives: energy, metals, agricultural and other commodities.
Derivatives that reference the basis between two risk factors and are denominated in a single currency11 (basis transactions) must be treated within separate hedging sets within the corresponding asset class. There is a separate hedging set12 for each pair of risk factors (ie for each specific basis). Examples of specific bases include threemonth Libor versus sixmonth Libor, threemonth Libor versus threemonth TBill, onemonth Libor versus overnight indexed swap rate, Brent Crude oil versus Henry Hub gas. For hedging sets consisting of basis transactions, the supervisory factor applicable to a given asset class must be multiplied by onehalf.
Derivatives that reference the volatility of a risk factor (volatility transactions) must be treated within separate hedging sets within the corresponding asset class. Volatility hedging sets must follow the same hedging set construction outlined in CRE52.45 (for example, all equity volatility transactions form a single hedging set). Examples of volatility transactions include variance and volatility swaps, options on realised or implied volatility. For hedging sets consisting of volatility transactions, the supervisory factor applicable to a given asset class must be multiplied by a factor of five.
The minimum time risk horizon for an unmargined transaction is the lesser of one year and the remaining maturity of the derivative contract, floored at ten business days.13 Therefore, the calculation of the effective notional for an unmargined transaction includes the following maturity factor, where M_{i} is the remaining maturity of transaction i, floored at 10 business days:
The maturity parameter (M_{i}) is expressed in years but is subject to a floor of 10 business days. Banks should use standard market convention to convert business days into years, and vice versa. For example, 250 business days in a year, which results in a floor of 10/250 years for M_{i}.
For margined transactions, the maturity factor is calculated using the margin period of risk (MPOR), subject to specified floors. That is, banks must first estimate the margin period of risk (as defined in CRE50.18) for each of their netting sets. They must then use the higher of their estimated margin period of risk and the relevant floor in the calculation of the maturity factor (CRE52.52). The floors for the margin period of risk are as follows:
Ten business days for noncentrallycleared transactions subject to daily margin agreements.
The sum of nine business days plus the remargining period for noncentrally cleared transactions that are not subject daily margin agreements.
The relevant floors for centrally cleared transactions are prescribed in the capital requirements for bank exposures to central counterparties (see CRE54).
The following are exceptions to the floors on the minimum margin period of risk set out in CRE52.50 above:
For netting sets consisting of more than 5000 transactions that are not with a central counterparty the floor on the margin period of risk is 20 business days.
For netting sets containing one or more trades involving either illiquid collateral, or an OTC derivative that cannot be easily replaced, the floor on the margin period of risk is 20 business days. For these purposes, "Illiquid collateral" and "OTC derivatives that cannot be easily replaced" must be determined in the context of stressed market conditions and will be characterised by the absence of continuously active markets where a counterparty would, within two or fewer days, obtain multiple price quotations that would not move the market or represent a price reflecting a market discount (in the case of collateral) or premium (in the case of an OTC derivative). Examples of situations where trades are deemed illiquid for this purpose include, but are not limited to, trades that are not marked daily and trades that are subject to specific accounting treatment for valuation purposes (eg OTC derivatives transactions referencing securities whose fair value is determined by models with inputs that are not observed in the market).
If a bank has experienced more than two margin call disputes on a particular netting set over the previous two quarters that have lasted longer than the applicable margin period of risk (before consideration of this provision), then the bank must reflect this history appropriately by doubling the applicable supervisory floor on the margin period of risk for that netting set for the subsequent two quarters.
The margin period of risk (MPOR_{i}) is often expressed in days, but the calculation of the maturity factor for margined netting sets references 1 year in the denominator. Banks should use standard market convention to convert business days into years, and vice versa. For example, 1 year can be converted into 250 business days in the denominator of the MF formula if MPOR is expressed in business days. Alternatively, the MPOR expressed in business days can be converted into years by dividing it by 250.
The supervisory correlation parameters (ρ_{i}) only apply to the PFE addon calculation for equity, credit and commodity derivatives, and are set out in Table 2 under CRE52.72. For these asset classes, the supervisory correlation parameters are derived from a singlefactor model and specify the weight between systematic and idiosyncratic components. This weight determines the degree of offset between individual trades, recognising that imperfect hedges provide some, but not perfect, offset. Supervisory correlation parameters do not apply to interest rate and foreign exchange derivatives.
As set out in CRE52.25, the aggregate addon for a netting set (AddOnaggregate) is calculated as the sum of the addons calculated for each asset class within the netting set. The sections that follow set out the calculation of the addon for each asset class.
The calculation of the addon for the interest rate derivative asset class captures the risk of interest rate derivatives of different maturities being imperfectly correlated. It does this by allocating trades to maturity buckets, in which full offsetting of long and short positions is permitted, and by using an aggregation formula that only permits limited offsetting between maturity buckets. This allocation of derivatives to maturity buckets and the process of aggregation (steps 3 to 5 below) are only used in the interest rate derivative asset class.
The addon for the interest rate derivative asset class (AddOnIR) within a netting set is calculated using the following steps:
Step 1: Calculate the effective notional for each trade in the netting set that is in the interest rate derivative asset class. This is calculated as the product of the following three terms: (i) the adjusted notional of the trade (d); (ii) the supervisory delta adjustment of the trade (δ); and (iii) the maturity factor (MF). That is, for each trade i, the effective notional D_{i} is calculated as D_{i} = d_{i} * MF_{i} * δ_{i}, where each term is as defined in CRE52.33 to CRE52.53.
Step 2: Allocate the trades in the interest rate derivative asset class to hedging sets. In the interest rate derivative asset class the hedging sets consist of all the derivatives that reference the same currency.
Step 3: Within each hedging set allocate each of the trades to the following three maturity buckets: less than one year (bucket 1), between one and five years (bucket 2) and more than five years (bucket 3).
Step 4: Calculate the effective notional of each maturity bucket by adding together all the trade level effective notionals calculated in step 1 of the trades within the maturity bucket. Let DB1, DB2 and DB3 be the effective notionals of buckets 1, 2 and 3 respectively.
Step 5: Calculate the effective notional of the hedging set (EN_{HS}) by using either of the two following aggregation formulas (the latter is to be used if the bank chooses not to recognise offsets between long and short positions across maturity buckets):
Step 6: Calculate the hedging set level addon (AddOn_{HS}) by multiplying the effective notional of the hedging set (EN_{HS}) by the prescribed supervisory factor (SF_{HS}). The prescribed supervisory factor in the interest rate asset class is set at 0.5%, which means that AddOn_{HS} = EN_{HS} * 0.005.
Step 7: Calculate the asset class level addon (AddOnIR) by adding together all of the hedging set level addons calculated in step 6:
The steps to calculate the addon for the foreign exchange derivative asset class are similar to the steps for the interest rate derivative asset class, except that there is no allocation of trades to maturity buckets (which means that there is full offsetting of long and short positions within the hedging sets of the foreign exchange derivative asset class).
The addon for the foreign exchange derivative asset class (AddOnFX) within a netting set is calculated using the following steps:
Step 1: Calculate the effective notional for each trade in the netting set that is in the foreign exchange derivative asset class. This is calculated as the product of the following three terms: (i) the adjusted notional of the trade (d); (ii) the supervisory delta adjustment of the trade (δ); and (iii) the maturity factor (MF). That is, for each trade i, the effective notional D_{i} is calculated as D_{i} = d_{i} * MF_{i} * δ_{i}, where each term is as defined in CRE52.33 to CRE52.53.
Step 2: Allocate the trades in the foreign exchange derivative asset class to hedging sets. In the foreign exchange derivative asset class the hedging sets consist of all the derivatives that reference the same currency pair.
Step 3: Calculate the effective notional of each hedging set (EN_{HS}) by adding together the trade level effective notionals calculated in step 1.
Step 4: Calculate the hedging set level addon (AddOn_{HS}) by multiplying the absolute value of the effective notional of the hedging set (EN_{HS}) by the prescribed supervisory factor (SF_{HS}). The prescribed supervisory factor in the foreign exchange derivative asset class is set at 4%, which means that AddOn_{HS} = EN_{HS} * 0.04.
Step 5: Calculate the asset class level addon (AddOnFX) by adding together all of the hedging set level addons calculated in step 5:
The calculation of the addon for the credit derivative asset class only gives full recognition of the offsetting of long and short positions for derivatives that reference the same entity (eg the same corporate issuer of bonds). Partial offsetting is recognised between derivatives that reference different entities in step 4 below. The formula used in step 4 is explained further in CRE52.62 to CRE52.64.
The addon for the credit derivative asset class (AddOnCredit) within a netting set is calculated using the following steps:
Step 1: Calculate the effective notional for each trade in the netting set that is in the credit derivative asset class. This is calculated as the product of the following three terms: (i) the adjusted notional of the trade (d); (ii) the supervisory delta adjustment of the trade (δ); and (iii) the maturity factor (MF). That is, for each trade i, the effective notional D_{i} is calculated as D_{i} = d_{i} * MF_{i} * δ_{i}, where each term is as defined in CRE52.33 to CRE52.53.
Step 2: Calculate the combined effective notional for all derivatives that reference the same entity. Each separate credit index that is referenced by derivatives in the credit derivative asset class should be treated as a separate entity. The combined effective notional of the entity (EN_{entity}) is calculated by adding together the trade level effective notionals calculated in step 1 that reference that entity.
Step 3: Calculate the addon for each entity (AddOn_{entity}) by multiplying the combined effective notional for that entity calculated in step 2 by the supervisory factor that is specified for that entity (SF_{entity}). The supervisory factors vary according to the credit rating of the entity in the case of single name derivatives, and whether the index is considered investment grade or noninvestment grade in the case of derivatives that reference an index. The supervisory factors are set out in Table 2 in CRE52.72.
Step 4: Calculate the asset class level addon (AddOnCredit) by using the formula that follows. In the formula the summations are across all entities referenced by the derivatives, AddOn_{entity} is the addon amount calculated in step 3 for each entity referenced by the derivatives and ρ_{entity} is the supervisory prescribed correlation factor corresponding to the entity. As set out in Table 2 in CRE52.72, the correlation factor is 50% for single entities and 80% for indices.
The formula to recognise partial offsetting in CRE52.61(4) above, is a singlefactor model, which divides the risk of the credit derivative asset class into a systematic component and an idiosyncratic component. The entitylevel addons are allowed to offset each other fully in the systematic component; whereas, there is no offsetting benefit in the idiosyncratic component. These two components are weighted by a correlation factor which determines the degree of offsetting/hedging benefit within the credit derivatives asset class. The higher the correlation factor, the higher the importance of the systematic component, hence the higher the degree of offsetting benefits.
It should be noted that a higher or lower correlation does not necessarily mean a higher or lower capital requirement. For portfolios consisting of long and short credit positions, a high correlation factor would reduce the charge. For portfolios consisting exclusively of long positions (or short positions), a higher correlation factor would increase the charge. If most of the risk consists of systematic risk, then individual reference entities would be highly correlated and long and short positions should offset each other. If, however, most of the risk is idiosyncratic to a reference entity, then individual long and short positions would not be effective hedges for each other.
The use of a single hedging set for credit derivatives implies that credit derivatives from different industries and regions are equally able to offset the systematic component of an exposure, although they would not be able to offset the idiosyncratic portion. This approach recognises that meaningful distinctions between industries and/or regions are complex and difficult to analyse for global conglomerates.
The calculation of the addon for the equity derivative asset class is very similar to the calculation of the addon for the credit derivative asset class. It only gives full recognition of the offsetting of long and short positions for derivatives that reference the same entity (eg the same corporate issuer of shares). Partial offsetting is recognised between derivatives that reference different entities in step 4 below.
The addon for the equity derivative asset class (AddOnEquity) within a netting set is calculated using the following steps:
Step 1: Calculate the effective notional for each trade in the netting set that is in the equity derivative asset class. This is calculated as the product of the following three terms: (i) the adjusted notional of the trade (d); (ii) the supervisory delta adjustment of the trade (δ); and (iii) the maturity factor (MF). That is, for each trade i, the effective notional D_{i} is calculated as D_{i} = d_{i} * MF_{i} * δ_{i}, where each term is as defined in CRE52.33 to CRE52.53.
Step 2: Calculate the combined effective notional for all derivatives that reference the same entity. Each separate equity index that is referenced by derivatives in the equity derivative asset class should be treated as a separate entity. The combined effective notional of the entity (EN_{entity}) is calculated by adding together the trade level effective notionals calculated in step 1 that reference that entity.
Step 3: Calculate the addon for each entity (AddOn_{entity}) by multiplying the combined effective notional for that entity calculated in step 2 by the supervisory factor that is specified for that entity (SF_{entity}). The supervisory factors are set out in Table 2 in CRE52.72 and vary according to whether the entity is a single name (SF_{entity} = 32%) or an index (SF_{entity} =20%).
Step 4: Calculate the asset class level addon (AddOnEquity) by using the formula that follows. In the formula the summations are across all entities referenced by the derivatives, AddOn_{entity} is the addon amount calculated in step 3 for each entity referenced by the derivatives and ρ_{entity} is the supervisory prescribed correlation factor corresponding to the entity. As set out in Table 2 in CRE52.72, the correlation factor is 50% for single entities and 80% for indices.
The supervisory factors for equity derivatives were calibrated based on estimates of the market volatility of equity indices, with the application of a conservative beta factor14 to translate this estimate into an estimate of individual volatilities.
Banks are not permitted to make any modelling assumptions in the calculation of the PFE addons, including estimating individual volatilities or taking publicly available estimates of beta. This is a pragmatic approach to ensure a consistent implementation across jurisdictions but also to keep the addon calculation relatively simple and prudent. Therefore, bank must only use the two values of supervisory factors that are defined for equity derivatives, one for single entities and one for indices.
The calculation of the addon for the commodity derivative asset class is similar to the calculation of the addon for the credit and equity derivative asset classes. It recognises the full offsetting of long and short positions for derivatives that reference the same type of underlying commodity. It also allows partial offsetting between derivatives that reference different types of commodity, however, this partial offsetting is only permitted within each of the four hedging sets of the commodity derivative asset class, where the different commodity types are more likely to demonstrate some stable, meaningful joint dynamics. Offsetting between hedging sets is not recognised (eg a forward contract on crude oil cannot hedge a forward contract on corn).
The addon for the commodity derivative asset class (AddOnCommodity) within a netting set is calculated using the following steps:
Step 1: Calculate the effective notional for each trade in the netting set that is in the commodity derivative asset class. This is calculated as the product of the following three terms: (i) the adjusted notional of the trade (d); (ii) the supervisory delta adjustment of the trade (δ); and (iii) the maturity factor (MF). That is, for each trade i, the effective notional D_{i} is calculated as D_{i} = d_{i} * MF_{i} * δ_{i}, where each term is as defined in CRE52.33 to CRE52.53.
Step 2: Allocate the trades in commodity derivative asset class to hedging sets. In the commodity derivative asset class there are four hedging sets consisting of derivatives that reference: energy, metals, agriculture and other commodities.
Step 3: Calculate the combined effective notional for all derivatives with each hedging set that reference the same commodity type (eg all derivative that reference copper within the metals hedging set). The combined effective notional of the commodity type (EN_{ComType}) is calculated by adding together the trade level effective notionals calculated in step 1 that reference that commodity type.
Step 4: Calculate the addon for each commodity type (AddOn_{ComType}) within each hedging set by multiplying the combined effective notional for that commodity calculated in step 3 by the supervisory factor that is specified for that commodity type (SF_{ComType}). The supervisory factors are set out in Table 2 in CRE52.72 and are set at 40% for electricity derivatives and 18% for derivatives that reference all other types of commodities.
Step 5: Calculate the addon for each of the four commodity hedging sets (AddOn_{HS}) by using the formula that follows. In the formula the summations are across all commodity types within the hedging set, AddOn_{ComType} is the addon amount calculated in step 4 for each commodity type and ρ_{ComType} is the supervisory prescribed correlation factor corresponding to the commodity type. As set out in Table 2 in CRE52.72, the correlation factor is set at 40% for all commodity types.
Step 6: Calculate the asset class level addon (AddOnCommodity) by adding together all of the hedging set level addons calculated in step 5:
Regarding the calculation steps above, defining individual commodity types is operationally difficult. In fact, it is impossible to fully specify all relevant distinctions between commodity types so that all basis risk is captured. For example crude oil could be a commodity type within the energy hedging set, but in certain cases this definition could omit a substantial basis risk between different types of crude oil (West Texas Intermediate, Brent, Saudi Light, etc). Also, the four commodity type hedging sets have been defined without regard to characteristics such as location and quality. For example, the energy hedging set contains commodity types such as crude oil, electricity, natural gas and coal. National supervisors may require banks to use more refined definitions of commodities when they are significantly exposed to the basis risk of different products within those commodity types.
Table 2 includes the supervisory factors, correlations and supervisory option volatility addons for each asset class and subclass.
Summary table of supervisory parameters 
Table 2 

Asset Class 
Subclass 
Supervisory factor 
Correlation 
Supervisory option volatility 

Interest rate 

0.50% 
N/A 
50% 

Foreign exchange 

4.0% 
N/A 
15% 

Credit, Single Name 
AAA 
0.38% 
50% 
100% 


AA 
0.38% 
50% 
100% 


A 
0.42% 
50% 
100% 


BBB 
0.54% 
50% 
100% 


BB 
1.06% 
50% 
100% 


B 
1.6% 
50% 
100% 


CCC 
6.0% 
50% 
100% 

Credit, Index 
IG 
0.38% 
80% 
80% 


SG 
1.06% 
80% 
80% 

Equity, Single Name 

32% 
50% 
120% 

Equity, Index 

20% 
80% 
75% 

Commodity 
Electricity 
40% 
40% 
150% 


Oil/Gas 
18% 
40% 
70% 


Metals 
18% 
40% 
70% 


Agricultural 
18% 
40% 
70% 


Other 
18% 
40% 
70% 

For a hedging set consisting of basis transactions, the supervisory factor applicable to its relevant asset class must be multiplied by onehalf. For a hedging set consisting of volatility transactions, the supervisory factor applicable to its relevant asset class must be multiplied by a factor of five.
If multiple margin agreements apply to a single netting set, the netting set must be divided into subnetting sets that align with their respective margin agreement. This treatment applies to both RC and PFE components.
If a single margin agreement applies to several netting sets, special treatment is necessary because it is problematic to allocate the common collateral to individual netting sets. The replacement cost at any given time is determined by the sum of two terms. The first term is equal to the unmargined current exposure of the bank to the counterparty aggregated across all netting sets within the margin agreement reduced by the positive current net collateral (ie collateral is subtracted only when the bank is a net holder of collateral). The second term is nonzero only when the bank is a net poster of collateral: it is equal to the current net posted collateral (if there is any) reduced by the unmargined current exposure of the counterparty to the bank aggregated across all netting sets within the margin agreement. Net collateral available to the bank should include both VM and NICA. Mathematically, RC for the entire margin agreement is calculated as follows, where:
where the summation NS ∈ MA is across the netting sets covered by the margin agreement (hence the notation)
V_{NS} is the current marktomarket value of the netting set NS and C_{MA} is the cash equivalent value of all currently available collateral under the margin agreement
Where a single margin agreement applies to several netting sets as described in CRE52.75 above, collateral will be exchanged based on marktomarket values that are netted across all transactions covered under the margin agreement, irrespective of netting sets. That is, collateral exchanged on a net basis may not be sufficient to cover PFE. In this situation, therefore, the PFE addon must be calculated according to the unmargined methodology. Netting setlevel PFEs are then aggregated using the following formula, where is the PFE addon for the netting set NS calculated according to the unmargined requirements:
Eligible collateral which is taken outside a netting set, but is available to a bank to offset losses due to counterparty default on one netting set only, should be treated as an independent collateral amount associated with the netting set and used within the calculation of replacement cost under CRE52.10 when the netting set is unmargined and under CRE52.18 when the netting set is margined. Eligible collateral which is taken outside a netting set, and is available to a bank to offset losses due to counterparty default on more than one netting set, should be treated as collateral taken under a margin agreement applicable to multiple netting sets, in which case the treatment under CRE52.75 and CRE52.76 applies. If eligible collateral is available to offset losses on nonderivatives exposures as well as exposures determined using the SACCR, only that portion of the collateral assigned to the derivatives may be used to reduce the derivatives exposure.